Готові списки джерел за темами / Method of detecting influences

Добірка наукової літератури з теми "Method of detecting influences"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 травня 2022

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Статті в журналах з теми "Method of detecting influences"

Guo, Weihong, Shucai Liu, Yaoning Liu, and Shuangshuang Chen. "Application of electrical resistivity imaging to detection of hidden geological structures in a single roadway." Open Geosciences 12, no. 1 (October 19, 2020): 1083–93. http://dx.doi.org/10.1515/geo-2020-0175.

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AbstractLocating concealed geological structures in coal seams on both sides of a coal mine excavation roadway is of vital importance for safe production. Conventional electrical resistivity imaging methods mostly arrange observation systems on the roadway roof and floor, so they are inevitably deficient when it comes to detecting concealed geological structures in coal seams. According to the electric field distribution characteristics of artificial field sources for electrical resistivity imaging methods and utilizing the shielding of current by roadway cavities, this paper proposes the parallel coal seam detection method that arranges observation systems in coal seams on the roadway side to detect concealed geological structures in coal seams. On the basis of introducing the principles of consequent detection methods, this paper investigates the influence of roadway cavities on observation results and offers a method of correcting the influence of roadway cavities. In view of the geoelectric characteristics of typical concealed geological structures in working faces, this paper establishes numerical models to verify the feasibility of the parallel coal seam detection method. As indicated by the calculation results, the consequent pole–dipole (A-MN) observation system is the most ideal in terms of dividing the geoelectric interfaces of concealed geological structures in working faces, and its detection effect is influenced significantly by the coal seam thickness and the electric differences between surrounding rock and anomalous bodies. Coal seam resistivity slightly influences detection of the consequent pole–dipole system. According to practical application effects, the parallel coal seam detection method can solve the problem of detecting concealed geological structures in “single-roadway” working faces.

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Genesca, A., L. Tusell, R. Alvarez, L. Ponsà, R. Miró, and J. Egozcue. "O-094. Methods of detecting genotoxic influences." Human Reproduction 12, Suppl_2 (June 1997): 44–45. http://dx.doi.org/10.1093/humrep/12.suppl_2.44-a.

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Hofer-Schmitz, Katharina, Ulrike Kleb, and Branka Stojanović. "The Influences of Feature Sets on the Detection of Advanced Persistent Threats." Electronics 10, no. 6 (March 17, 2021): 704. http://dx.doi.org/10.3390/electronics10060704.

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This paper investigates the influences of different statistical network traffic feature sets on detecting advanced persistent threats. The selection of suitable features for detecting targeted cyber attacks is crucial to achieving high performance and to address limited computational and storage costs. The evaluation was performed on a semi-synthetic dataset, which combined the CICIDS2017 dataset and the Contagio malware dataset. The CICIDS2017 dataset is a benchmark dataset in the intrusion detection field and the Contagio malware dataset contains real advanced persistent threat (APT) attack traces. Several different combinations of datasets were used to increase variety in background data and contribute to the quality of results. For the feature extraction, the CICflowmeter tool was used. For the selection of suitable features, a correlation analysis including an in-depth feature investigation by boxplots is provided. Based on that, several suitable features were allocated into different feature sets. The influences of these feature sets on the detection capabilities were investigated in detail with the local outlier factor method. The focus was especially on attacks detected with different feature sets and the influences of the background on the detection capabilities with respect to the local outlier factor method. Based on the results, we could determine a superior feature set, which detected most of the malicious flows.

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Yang, Ya-xun, Wen-hao Chai, De-chuang Liu, Wei-de Zhang, Jia-cheng Lu, and Zhi-kui Yang. "An Impact-Echo Experimental Approach for Detecting Concrete Structural Faults." Advances in Civil Engineering 2021 (December 20, 2021): 1–8. http://dx.doi.org/10.1155/2021/8141015.

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For the current problem of detection of grouting defects in posttensioned prestressed concrete members, the paper takes a single-layer arrangement of prestressed pipes as the object of study. The influence law of the main factors such as pipe material, defect size, defect critical surface location, and prestressing reinforcement location on the results of the impact-echo method for detecting concrete grouting defects was studied. Firstly, the ABAQUS finite element software was used to simulate these factors to obtain the influence law on the detection results, and a modal test was conducted to verify them. The results show that the impact-echo method can effectively test the location of defects and the degree of burial depth, and the pipe material influences the test results, and the impact of corrugated metal pipe is smaller and more accurate than the PVC pipe. In addition, the greater the plate thickness frequency drift rate, the larger the transverse size of the defect, so the plate thickness frequency drift rate and the measured defect depth are combined to quantitatively determine the depth of the defect.

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Moro, Bruna L. P., Tatiane F. Novaes, Laura R. A. Pontes, Thais Gimenez, Juan S. Lara, Daniela P. Raggio, Mariana M. Braga, and Fausto M. Mendes. "The Influence of Cognitive Bias on Caries Lesion Detection in Preschool Children." Caries Research 52, no. 5 (2018): 420–28. http://dx.doi.org/10.1159/000485807.

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We aimed to evaluate whether children’s caries experience exerts an influence on the performance of visual and radiographic methods in detecting nonevident proximal caries lesions in primary molars. Eighty children (3–6 years old) were selected and classified as having a lower (≤3 decayed, missing, or filled surfaces; dmf-s) or higher (> 3 dmf-s) caries experience. Two calibrated examiners then assessed 526 proximal surfaces for caries lesions using visual and radiographic methods. As a reference standard, 2 other examiners checked the surfaces after temporary separation. Noncavitated and cavitated lesion thresholds were considered and Poisson multilevel regression analyses were conducted to evaluate the influence of caries experience on the performance of diagnostic strategies. Accuracy parameters stratified by caries experience were also derived. A statistically significant influence of caries experience was observed only for visual inspection, with more false-positive results in children with a higher caries experience at the noncavitated lesion threshold, and more false results at the cavitated threshold. The detection of noncavitated caries lesions in children with a higher caries experience was overestimated (specificity = 0.696), compared to children with a lower caries experience (specificity = 0.918), probably due to confirmation bias. However, the examiners underestimated the detection of cavitated lesions in children with a higher caries experience (sensitivity = 0.143) compared to lower-caries-experience children (sensitivity = 0.222), possibly because of representativeness bias. The radiographic method was not influenced by children’s caries experience. In conclusion, children’s caries experience influences the performance of visual inspection in detecting proximal caries lesions in primary teeth, evidencing the occurrence of cognitive biases.

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Yang, Zhihai, and Zhongmin Cai. "Detecting Anomalous Ratings in Collaborative Filtering Recommender Systems." International Journal of Digital Crime and Forensics 8, no. 2 (April 2016): 16–26. http://dx.doi.org/10.4018/ijdcf.2016040102.

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Online rating data is ubiquitous on existing popular E-commerce websites such as Amazon, Yelp etc., which influences deeply the following customer choices about products used by E-businessman. Collaborative filtering recommender systems (CFRSs) play crucial role in rating systems. Since CFRSs are highly vulnerable to “shilling” attacks, it is common occurrence that attackers contaminate the rating systems with malicious rates to achieve their attack intentions. Despite detection methods based on such attacks have received much attention, the problem of detection accuracy remains largely unsolved. Moreover, few can scale up to handle large networks. This paper proposes a fast and effective detection method which combines two stages to find out abnormal users. Firstly, the manuscript employs a graph mining method to spot automatically suspicious nodes in a constructed graph with millions of nodes. And then, this manuscript continue to determine abnormal users by exploiting suspected target items based on the result of first stage. Experiments evaluate the effectiveness of the method.

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Bartsch, Sarah M., Kim F. Wong, Owen J. Stokes-Cawley, James A. McKinnell, Chenghua Cao, Gabrielle M. Gussin, Leslie E. Mueller, et al. "Knowing More of the Iceberg: How Detecting a Greater Proportion of Carbapenem-Resistant Enterobacteriaceae Carriers Influences Transmission." Journal of Infectious Diseases 221, no. 11 (November 5, 2019): 1782–94. http://dx.doi.org/10.1093/infdis/jiz288.

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Abstract Background Clinical testing detects a fraction of carbapenem-resistant Enterobacteriaceae (CRE) carriers. Detecting a greater proportion could lead to increased use of infection prevention and control measures but requires resources. Therefore, it is important to understand the impact of detecting increasing proportions of CRE carriers. Methods We used our Regional Healthcare Ecosystem Analyst–generated agent-based model of adult inpatient healthcare facilities in Orange County, California, to explore the impact that detecting greater proportions of carriers has on the spread of CRE. Results Detecting and placing 1 in 9 carriers on contact precautions increased the prevalence of CRE from 0% to 8.0% countywide over 10 years. Increasing the proportion of detected carriers from 1 in 9 up to 1 in 5 yielded linear reductions in transmission; at proportions >1 in 5, reductions were greater than linear. Transmission reductions did not occur for 1, 4, or 5 years, varying by facility type. With a contact precautions effectiveness of ≤70%, the detection level yielding nonlinear reductions remained unchanged; with an effectiveness of >80%, detecting only 1 in 5 carriers garnered large reductions in the number of new CRE carriers. Trends held when CRE was already present in the region. Conclusion Although detection of all carriers provided the most benefits for preventing new CRE carriers, if this is not feasible, it may be worthwhile to aim for detecting >1 in 5 carriers.

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Daxiang, X., T. Debao, W. Xiongfei, and W. Qiao. "A Dynamic Threshold Cloud Detecting Approach based on the Brightness Temperature from FY-2 VISSR Data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 617–25. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-617-2015.

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The traditional statistical methods and radiation transfer theory methods for cloud detecting have a high adaptability just only in those areas with a uniform surface coverage and noncomplex terrain. Therefore, adapted to large spatial and temporal scales, in this work a cloud detection method is developed, seeking the main influencing factors of the change of Brightness Temperature(BT) of clear sky and their relationships, researching the change regularity and normal fluctuation range of BT on the basis of function fitting, setting the cloud detecting dynamic threshold depending on the cloud spectral characteristics, and making accuracy assessment in order to ensure higher adaptability and accuracy of this cloud detecting method. In this paper, a dynamic threshold algorithm is presented for cloud detection using daytime imagery from the VISSR sensor on board FY-2C/D/E, which is the first generation geostationary satellite. And the land surface/brightness temperature influence functions are analysis and established, including latitude, longitude, altitude, time, land cover. The theoretical temperature value of clear sky can be calculated through these influence functions. Then, the dynamic threshold cloud detection model is proposed based on the high temporal resolution of VISSR data. Meanwhile, the land surface emissivity is considered as the main factor to the change range of brightness temperature which determines the dynamic threshold for cloud detection. Finally, the dynamic threshold cloud detecting model is evaluated using FY-2C/D/E VISSR data covering China, and the Kappa of dynamic method is maximum, equalling 0.6195, which is much higher than the indexes for the reflectivity and BT fixed methods, equalling 0.4511 and 0.403, respectively. Consequently, the dynamic threshold cloud detecting method provides an important improvement because the spatial, temporal and geographic characteristics were considered into the model.

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Zhong, Yan Hui, Bei Zhang, Ming Ming Ren, Cheng Chao Guo, and Chu Chu Xia. "Method of Analyzing the Size of Voids Beneath Rigid Pavement Slabs." Advanced Materials Research 418-420 (December 2011): 1516–19. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.1516.

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The size of voids beneath rigid pavement slabs is an important factor which influences the bearing capacity of roads. GPR is an advanced method for detecting voids beneath rigid pavement slabs. Combined with drilling and sampling, equations including parameters of GPR wave amplitude, horizontal size and vertical size of voids are established for analyzing the size of voids. Then, based on the equations, the horizontal size and vertical size of voids can be calculated according to the actual GPR wave amplitude.

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He, Yong, and Zhongmin Cui. "Evaluating Robust Scale Transformation Methods With Multiple Outlying Common Items Under IRT True Score Equating." Applied Psychological Measurement 44, no. 4 (November 15, 2019): 296–310. http://dx.doi.org/10.1177/0146621619886050.

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Item parameter estimates of a common item on a new test form may change abnormally due to reasons such as item overexposure or change of curriculum. A common item, whose change does not fit the pattern implied by the normally behaved common items, is defined as an outlier. Although improving equating accuracy, detecting and eliminating of outliers may cause a content imbalance among common items. Robust scale transformation methods have recently been proposed to solve this problem when only one outlier is present in the data, although it is not uncommon to see multiple outliers in practice. In this simulation study, the authors examined the robust scale transformation methods under conditions where there were multiple outlying common items. Results indicated that the robust scale transformation methods could reduce the influences of multiple outliers on scale transformation and equating. The robust methods performed similarly to a traditional outlier detection and elimination method in terms of reducing the influence of outliers while keeping adequate content balance.

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Більше джерел

Дисертації з теми "Method of detecting influences"

Кущ, Віталій Сергійович. "Метод підбору та виявлення впливів релаксуючих картин для коригування психофізіологічного стану людини". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/39383.

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Робота містить 70 сторінок, 25 рисунківта 19 таблиць. Було використано 12 джерел. Мета роботи: підвищити швидкість та ефективність дослідження та коригування психофізіологічного стану людини за рахунок розробки методу підбору та виявлення впливів релаксуючих картин для коригування психофізіологічного стану людини. Проведено огляд основних положень проведення досліджень, збору даних та коригування психофізіологічного стану людини. Описано основні проблеми обробки зібраних даних для аналізу, підбору релаксуючих картин та визначено необхідність у розробці методів для підбору та визначення впливів на психофізіологічний стан релаксуючих картин. Запропоновано метод підбору релаксуючих картин для коригування психофізіологічного стану людини на основі нейронних мереж. Застосування запропонованого методу дозволяє подати на вхід набір параметрів: кольорову преференцію, день народжень, суб’єктивні відчуття та отримати на виході релаксуючу картину для проведення сеансів коригування психофізіологічного стану. Запропоновано метод виявлення впливів на психофізіологічний стан людини, який дозволяє, за рахунок гнучкого механізму конфігурації побудови графіків, будувати різноманітні параметри дослідження психофізіологічного стану людини та виявляти їх залежності та впливи на людину. Розроблено програмне забезпечення запропонованих методів підбору та виявлення впливів релаксуючих картин на стан людини, яке збільшує ефективність роботи психологів з дослідження психофізіологічного стану людини, за рахунок швидких та точних обчислень. Розроблено стартап-проект програмного забезпечення та проведено аналіз ринку, потенційних клієнтів, з якого видно, що ринок поки вільний від аналогів такого продукту, але має у ньому потребу.
The work contains 70 pages, 25 figures, and 19 tables. 12 sources have been used. Goal: to increase the speed and efficiency of research and adjustment of the psychophysiological state of a person by developing a method of matching and detecting influences of relaxing pictures for human psychophysiological state adjustment. A review of the main provisions of research, data collection, and adjustment of the psychophysiological state of humans. The main problems of processing the collected data for the analysis, matching of relaxing pictures are described and the necessity in the development of methods for matching and detecting influences on a psychophysiological condition of relaxing pictures is defined. A method of matching relaxing pictures for correction of the psychophysiological state of a human on the basis of neural networks is offered. The application of the proposed method allows you to submit a set of parameters: color preference, birthday, favorite color, subjective feelings and get a relaxing picture for sessions to correct the psychophysiological state. A method for detecting influences on the psychophysiological state of a person is proposed, which allows, due to a flexible configuration mechanism for plotting, to build various parameters of research of the psychophysiological state of a person and identify their dependencies and influences on a person. The software of the offered methods of matching and detecting influences of relaxing pictures on a condition of the human which increases the efficiency of work of psychologists on the research of a psychophysiological condition of the person is developed. A software startup project has been developed and an analysis of potential customers and the market has been conducted, which shows that the market is still free from analogs of such a product, but needs it.

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Elva, Rochelle. "Detecting Semantic Method Clones in Java Code using Method IOE-Behavior." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5731.

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The determination of semantic equivalence is an undecidable problem; however, this dissertation shows that a reasonable approximation can be obtained using a combination of static and dynamic analysis. This study investigates the detection of functional duplicates, referred to as semantic method clones (SMCs), in Java code. My algorithm extends the input-output notion of observable behavior, used in related work [1, 2], to include the effects of the method. The latter property refers to the persistent changes to the heap, brought about by the execution of the method. To differentiate this from the typical input-output behavior used by other researchers, I have coined the term method IOE-Behavior; which means its input-output and effects behavior [3]. Two methods are defined as semantic method clones, if they have identical IOE-Behavior; that is, for the same inputs (actual parameters and initial heap state), they produce the same output (that is result- for non-void methods, and final heap state). The detection process consists of two static pre-filters used to identify candidate clone sets. This is followed by dynamic tests that actually run the candidate methods, to determine semantic equivalence. The first filter groups the methods by type. The second filter refines the output of the first, grouping methods by their effects. This algorithm is implemented in my tool JSCTracker, used to automate the SMC detection process. The algorithm and tool are validated using a case study comprising of 12 open source Java projects, from different application domains and ranging in size from 2 KLOC (thousand lines of code) to 300 KLOC. The objectives of the case study are posed as 4 research questions: 1. Can method IOE-Behavior be used in SMC detection? 2. What is the impact of the use of the pre-filters on the efficiency of the algorithm? 3. How does the performance of method IOE-Behavior compare to using only input-output for identifying SMCs? 4. How reliable are the results obtained when method IOE-Behavior is used in SMC detection? Responses to these questions are obtained by checking each software sample with JSCTracker and analyzing the results. The number of SMCs detected range from 0 45 with an average execution time of 8.5 seconds. The use of the two pre-filters reduces the number of methods that reach the dynamic test phase, by an average of 34%. The IOE-Behavior approach takes an average of 0.010 seconds per method while the input-output approach takes an average of 0.015 seconds. The former also identifies an average of 32% false positives, while the SMCs identified using input-output, have an average of 92% false positives. In terms of reliability, the IOE-Behavior method produces results with precision values of an average of 68% and recall value of 76% on average. These reliability values represent an improvement of over 37% (for precision) of the values in related work [4]. Thus, it is my conclusion that IOE-Behavior can be used to detect SMCs in Java code with reasonable reliability.
Ph.D.
Doctorate
Computer Science
Engineering and Computer Science
Computer Science

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Kalmar, Gabriel Bela. "A non-radioactive method of detecting nucleic acids." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/25896.

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Monoclonal antibodies (MCAs) specific for iodinated cytidine were produced and characterized for their possible application in the development of a serological, non-radioactive assay for nucleic acids. The method requires the modification of single-stranded ribonucleic acid (ss-RNA) by addition of an iodine to the C-5 position of cytidine via the Commerford reaction.. The level of iodination was followed by ultraviolet (UV) spectroscopy and X-ray diffraction (XRF) and was found to be higher for polyC than for cellular RNA or ss-RNA of southern bean mosaic and cowpea chlorotic mottle virus. No evidence was obtained for iodination of double-stranded (ds) RNA of turnip yellow mosaic virus. Only one hybridoma, (Rl), of 2,500, tested secreted MCAs specific for iodinated cytidine. The specificity and affinity of this MCA for iodinated and non-iodinated synthetic polynucleotides and iodinated cellular ss-RNA were assessed by solid-phase and inhibition assays, using the enzyme-1 inked immunosorbent assay (ELISA). Seven other hybridomas produced MCAs with varying specificities for iodinated nucleotide-carrier combinations. 'The binding of MCA Rl to iodocytidine-carrier was inhibited by iodocytidine or iodocytidine-5'-phosphate and by adenosine or adenosine-5'-phosphate (20 and 200 times less so, respectively) but not by guanosine, thymidine, and uridine, or their monophosphates. As little as 5 ng of iodocytidine-carrier bound to a nitrocellulose membrane could be detected by MCA Rl in an immune-blot assay whereas no reaction was observed with 1-1000 ng of cytidine-carrier. The lower levels of detection for iodinated cellular nucleic acid and iodinated polyC were 50 and 25 ng, respectively, in the same assay. The method may have applications in the development of a serological, non-radioactive assay for nucleic acids.
Land and Food Systems, Faculty of
Graduate

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Watson, Garrett (Garrett A. ). "A method for detecting nonequilibrium dynamics in active matter." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120209.

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Thesis: S.B., Massachusetts Institute of Technology, Department of Physics, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 55-56).
Active force generation is an important class of out-of-equilibrium activity in cells. These forces play a crucial role in vital processes such as tissue folding, cell division and intracellular transport. It is important to determine the extent of such nonequilibrium activity during cellular processes to understand cell function. Here we present a framework for measuring nonequilibrium activity in biological active matter using time reversal asymmetry based on the Kullbeck-Leibler Divergence (KLD), also known as relative entropy. We estimate the KLD from a stationary time series using a k-nearest neighbors estimator, comparing the time-forwards process to the time-reversed process Using time series data of probe particles embedded in the actin cortex, we establish a lower bound for the entropy production of cortical activity. Our results demonstrate a reliable way to measure the breaking of detailed balance in mesoscopic systems.
by Garrett Watson.
S.B.

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Tasooji, Mohammad. "Novel Liquid extraction method for detecting Native-wood Formaldehyde." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/73511.

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New vigorous regulations have been established for decreasing the allowable formaldehyde emissions from nonstructural wood based composites. Two main sources of formaldehyde emission in non-structural wood based composites are adhesive and wood. Adhesives are quite well known and great efforts have been conducted to decrease their formaldehyde content; however formaldehyde emission from wood has received little attention and it is not completely understood. Wood-borne formaldehyde emission exists in a complex equilibrium in wood matrix. The reaction between formaldehyde and wood hydroxyl groups/water can hinder the complete formaldehyde extraction. In order to have a complete formaldehyde extraction, a stronger nucleophile than hydroxyl and water groups is needed. In this study cross-linked poly (allylamine) (PAA) beads were synthesized and used as a strong nucleophile to extract all the biogenic and synthetic free-formaldehyde within the woody matrix of never-heated and heat-treated Virginia pines; the results were compared to simple water extraction. A new formaldehyde capturing device was also developed using a serum bottle. Results showed that there was no advantage of using PAA beads over simple water extraction for extracting woody matrix free-formaldehyde. This means that simple water extraction can extract all the free-formaldehyde from the woody matrix. It was also found that thermal treatment resulted in generating more wood-borne formaldehyde. The other important finding was the new developed formaldehyde capturing device. The device was very promising for detecting wood-borne formaldehyde from very small pieces of wood (5-70 mg) and can be very useful in future studies.
Master of Science

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Gao, Chunwang. "Statisical method and simulation on detecting cracks in vibrothermography inspection." [Ames, Iowa : Iowa State University], 2010. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3403798.

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Jung, Jeenah. "Development of optical imaging method for detecting RNA-protein interactions." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54278.

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The localization and translation of messenger ribonucleic acids (mRNAs) play crucial roles in cellular function and diseases, and are regulated by numerous RNA-binding proteins (RBPs) and small non-coding RNAs, called trans-acting factors. Biochemical and imaging methods used to study RNA interactions with these trans-acting elements have made important discoveries in characterizing how these factors regulate gene expression and determining the RNA sequence to which they bind. However, the spatiotemporal information regarding these interactions in subcellular compartments have been difficult to determine or to quantify accurately. To image and quantify native RNA and RNA–protein interactions simultaneously in situ, we developed a proximity ligation assay that combines peptide-modified RNA imaging probes. It can detect the RNAs in live cells and the interactions at a single-interaction level. Lastly, it can produce results that are easily quantifiable. We tested the specificity and sensitivity of this technique using two models: interactions between the genomic RNA and the N protein of human respiratory syncytial virus as well as those between exogenous transcripts with or without the Human antigen R (HuR) binding site and HuR. To validate this method, its accuracy and utility have been demonstrated in three models: poly(A)+ or β-actin mRNAs binding to different cytoskeleton for localization, poly(A)+ or β-actin mRNAs interacting with HuR for stabilization, and programmed cell death 4 (PDCD4) mRNA binding to HuR or T-cell intracellular antigen (TIA1) for translational regulation.

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Serra, Andreas. "A difference analysis method for detecting differences between similar documents." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-219566.

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Similarity analysis of documents is a well studied field. With a focus instead on the opposite concept, how can we try to define and distinguish the differences within documents? This project tries to determine if differences within documents can be detected as well as quantified based on their semantic qualities. We propose a method for quantifying differences by applying tf-idf based models with analysis methods for lemmatization and synonym extraction, together with utility ranking algorithms. The method is implemented and tested. The results show that the method has potential but that further studies are required in order to fully evaluate to what extent it could be of practical use. Such a method could though reap significant benefits within several different fields in which automatic difference detection could replace error prone manual labor in document management, as well as other beneficial purposes such as to provide automatically generated difference summaries.
Likhetsanalys mellan dokument är ett välutforskat område. Med fokus istället på motsatsen, hur kan vi försöka definiera och särskilja skillnaderna mellan dokument? Detta projekt försöker undersöka om skillnader mellan dokument kan detekteras samt kvantifieras baserat på deras semantiska kvalitéer. Vi föreslår en metod för kvantifiering av skillnader genom att applicera tf-idf baserade modeller tillsammans med analysmetoder för lemmatisering och synonymextrahering, i kombination med utilitetsrankningsalgoritmer. Metoden implementeras och testas. Resultaten visar att metoden har potential men att det krävs ytterligare studier för att fullt ut avgöra till vilken grad den skulle kunna vara praktiskt användbar. En sådan metod skulle dock kunna erbjuda stora fördelar för ett flertal olika discipliner, där automatisk skillnadsdetektering skulle kunna ersätta felbenägen manuellt arbete gällande dokumentationshantering, samt också fylla andra förmånliga syften som t.ex. att kunna erbjuda automatgenererade skillnadssammanfattningar.

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Saleh, Ahmed Dhary. "Development of a method for detecting TB-antibodies in patient serum." Thesis, Bangor University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.664479.

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The main objective of the work was to develop a analytical method for the diagnosis of TB, and this was achieved in three parts.The first part was involved the synthesis of two oxygenated mycolic acids, a methoxy mycolic acid (I) and a keto mycolic acid (11). The successful synthesis of these mycolic acids led to the synthesis of the cord factors TDM (Ill), TMM (IV), TDM (V) and TMM (VI), which were used in modified ELISA assay as new antigens to detect TB-antibodies in serum. The second part was involved the synthesis of thiolated derivatives (VII), (VIII) and (IX) of methoxy mycolic acids. These compounds will be covalently attached to a gold surface so as to create a self assembled monolayer with antigenic properties. It is expected that this will create a stable surface for the binding of TB-antibodies in diagnosis tuberculosis tests. This will contribute to development of a new biosensor as a rapid and accurate method for detecting TB infection. The third part was concerned on analysing of TB positive and TB negative samples to detect TB-antibodies in patient serum using novel synthetic mycolic acids and their derivatives as antigens in modified ELISA assay, after determination of the optimisation conditions of the ELISA assay. Higher antibody binding signals were observed with cord factors. The sensitivity and selectivity for TDM (198) (80%, 87%), TDM (204) (75%, 90%) and TDM (254) (80%, 84%), respectively which showed good significant values in comparison with other synthetic antigens.

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Rahimi, Sanaz. "A method for detecting and locating brain tumors in MRI images /." Available to subscribers only, 2007. http://proquest.umi.com/pqdweb?did=1467892381&sid=21&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Книги з теми "Method of detecting influences"

Moffett, James. Detecting growth in language. Portsmouth, N.H: Boynton/Cook, 1992.

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Guttman, Irwin. Bayesian method of detecting change point in regression and growth curve models. Toronto: University of Toronto, Dept. of Statistics, 1985.

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Fiol-Matta, Liana. Civil law and common law in the legal method of Puerto Rico. [Puerto Rico: L. Fiol-Matta], 1996.

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Developmental influences on adult intelligence: The seattle longitudinal study. 2nd ed. New York, NY: Oxford University Press, 2012.

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Tragedia e storia: Arnold Toynbee, la storia universale nella maschera della classicità. Roma: Aracne editrice S.r.l., 2014.

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Kwaśniak, Mieczysław. Badanie wpływu niezawodności wewnętrznej sieci geodezyjnej na efektywność wybranych podejść do wykrywania błędow grubych: Research on the influence of internal reliability of geodetic network on the effectiveness of selected approaches to gross errors detection. Warszawa: Oficyna Wydawnicza Politechniki Warszawskiej, 2012.

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Symonds, Lynne M. An enquiry into the effects of the current reporting method in Hethersett Old Hall School with particular referenceto the influences of various aspects of reporting on learning in science. [Guildford]: [University of Surrey], 1990.

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Printing, London College of. BA MPD Design History thesis 1986: Pargetting.A traditional East Anglian craft,the influences behind its evolution and development as a method of architectural decoration in the sixteenth and seventeenth centuries. London: London College of Printing, 1986.

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Kenkyūjo, Kokuritsu Kankyō. Gurōbaru na DNA mechiru-ka henka ni chakumokushita kankyō kagaku busshitsu no epijenetikusu sayō sukurīningu-hō no kaihatsu: Kankyōshō kankyō kenkyū gijutsu kaihatsu suishinhi shūryō kenkyū seika hōkokusho : Heisei 20-nendo--Heisei 21-nendo = Studies on the method for detecting epigenetics effects of environmental chemicals focusing on global changes of DNA methylation. [Tokyo]: Kankyōshō Sōgō Kankyō Seisakukyoku Kankyō Hokenbu Kankyō Anzenka Kankyō Risuku Hyōkashitsu, 2010.

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Kesoretskikh, Ivan, and Sergey Zotov. Landscape vulnerability: concept and assessment. ru: INFRA-M Academic Publishing LLC., 2019. http://dx.doi.org/10.12737/1045820.

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The monograph presents a methodology for assessing the vulnerability of landscapes to external influences. A comparative analysis of the concepts of "stability", "sensitivity", "vulnerability" in relation to natural complexes. An overview of existing methods for assessing the vulnerability of natural complexes is presented. The author's method of assessing the vulnerability of landscapes to anthropogenic impacts is described. The methodology is based on: selection and justification of criteria for assessing the vulnerability of landscapes; preparation of a parametric matrix and gradation of assessment criteria in accordance with the developed vulnerability classes; calculation of weighting factors of vulnerability assessment parameters; selection of optimal territorial operational unit for landscape vulnerability assessment. The method is implemented in the GIS environment "Assessment of vulnerability of landscapes of the Kaliningrad region to anthropogenic impacts", created by the authors using modern geoinformation products. The specificity of spatial differentiation of different landscapes in terms of vulnerability to anthropogenic impacts at the regional and local levels is revealed. It is stated that the use of the methodology for assessing the vulnerability of landscapes to anthropogenic impacts and its integration into the system of nature management will ensure a balanced account of geoecological features and environmental priorities in territorial planning. It is of interest to specialists in the field of rational nature management, environmental protection, spatial planning.

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Porwik, Piotr, and Lukasz Wieclaw. "Fingerprint Reference Point Detection Using Neighbourhood Influence Method." In Advances in Soft Computing, 786–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75175-5_97.

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Rozenberg, Boris, Ehud Gudes, Yuval Elovici, and Yuval Fledel. "Method for Detecting Unknown Malicious Executables." In Lecture Notes in Computer Science, 376–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04342-0_31.

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Fan, Tao, Jianhua Peng, Haiwu Zhao, and Guozhong Wang. "An Automatic TV LOGO Detecting Method." In Communications in Computer and Information Science, 236–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34595-1_33.

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Hatzes, Artie P. "The Radial Velocity Method for the Detection of Exoplanets." In Methods of Detecting Exoplanets, 3–86. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27458-4_1.

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Kindermann, Christian, Bijan Parsia, and Uli Sattler. "Detecting Influences of Ontology Design Patterns in Biomedical Ontologies." In Lecture Notes in Computer Science, 311–28. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30793-6_18.

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Utikal, Klaus J. "A Nonparametric Method for Detecting Neural Connectivity." In Statistical Modelling, 287–95. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-0789-4_35.

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Kim, Chong Hee, and Jean-Jacques Quisquater. "Method for Detecting Vulnerability to Doubling Attacks." In Information and Communications Security, 97–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88625-9_7.

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Bhardwaj, Dinesh, Chothmal Kumawat, and Vinod Pankajakshan. "A Method for Detecting JPEG Anti-forensics." In Communications in Computer and Information Science, 190–97. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0020-2_17.

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MacRitchie, Finlay. "How the media influences public thinking." In The Need for Critical Thinking and the Scientific Method, 53–64. Boca Raton : Taylor & Francis, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9781351255875-5.

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Tatara, Kohei, Toshihiro Tabata, and Kouichi Sakurai. "A Probabilistic Method for Detecting Anomalous Program Behavior." In Information Security Applications, 87–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31815-6_8.

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Тези доповідей конференцій з теми "Method of detecting influences"

Yu, Zexing, Fei Du, and Chao Xu. "Time-Domain Spectral Element Simulation of Lamb Wave Time Reversal Method for Detecting a Breathing Crack in a Plate." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10495.

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Abstract Lamb wave is considered as an appropriate approach to detect the cracks in structures. This paper combines an efficient time-domain spectral finite element with time reversal method to develop an efficient breathing crack detection method. In this regard, Gauss-Lobatto-Legendre quadrature rules and penalty function method are carried out to construct an effective and accurate approach. Comparing the computation scales and results of this method and traditional finite element method, the validity and superiority of the proposed model is stressed. The reconstructed signals of two scenarios, intact and impaired structures, are captured. It is concluded that, this approach is capable of detecting breathing cracks. In addition, the influences of the relative depth of the notch and incident region are studied. This research may provide the guidance for experiment configuration and the further study.

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Tereshin, Vladimir, Tatyana Tyulkova, Tatyana Umpeleva, Natalya Yeremeeva, Diana Vakhrusheva, Kseniya Belousova, and Valeria Guseva. "Influence of genotype of MBT on the method of detecting tuberculosis." In ERS International Congress 2019 abstracts. European Respiratory Society, 2019. http://dx.doi.org/10.1183/13993003.congress-2019.pa4623.

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Wei, Wei, Jun Wang, and Haiying Wang. "Method for Detecting Nodes Influence Who Occupy Structural Holes in Temporal Network." In 2019 5th International Conference on Information Management (ICIM). IEEE, 2019. http://dx.doi.org/10.1109/infoman.2019.8714706.

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Mei, Wei-Ping, and Fritz A. Popp. "Low-level luminescence as a method of detecting the UV influence on biological systems." In International Symposium on Biomedical Optics Europe '94, edited by Anna M. Verga Scheggi, Francesco Baldini, Pierre R. Coulet, and Otto S. Wolfbeis. SPIE, 1995. http://dx.doi.org/10.1117/12.201246.

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Hashimura, Shinji, Kai Kubota, Nozomu Ohmi, and Kyoichi Komatsu. "Robustness of Detection Method for Clamp Force Against Configuration Error in Bolt/Nut Assemblies." In JSME 2020 Conference on Leading Edge Manufacturing/Materials and Processing. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/lemp2020-8605.

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Abstract Reliability of bolt/nut assemblies directly influences the quality of machines and structures. It is most important to control and maintain the clamp force of bolt/nut assemblies to secure reliability. However it is not easy to control the clamp force during tightening. And it is also difficult to detect the clamp force after tightening. In our previous study, we proposed a method to easily detect the clamp force of bolt/nut assemblies that have already been tightened. In the method, the bolt thread portion protruding from the nut is pulled while supporting the nut’s upper surface. The relationship between the tensile force and the displacement at the pulling point differs before and after the tensile force reaches the clamp force. The method can detect the tensile force at the point where the relationship changes as the clamp force. In this study, robustness of the detection method for the squareness error of the bearing surface of clamped parts has been investigated by FE analysis and experiments. The results of the FE analysis showed that the squareness error of the bolt bearing surface does not have an influence on the detection accuracy. The results indicate that the detection method has robustness for the squareness error of bolt bearing surfaces. Contrary to that, the experimental results show that the squareness error does have a clear influence on the detection accuracy. The averages of detection error in the experiments increased about 10% with an increase in squareness error. It is considered that the error was caused because the mating thread surfaces did not separate when the tensile force reached the clamp force.

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Giesecke, Daniel, Jens Friedrichs, Thomas Kenull, Matthias Binner, and Martin Siegert. "A Method for Forecasting the Condition of HPT NGVs by Using Bayesian Belief Networks and a Statistical Approach." In ASME Turbo Expo 2014: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gt2014-25464.

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Jet engine maintenance is a very competitive field in terms of time and costs. To increase planning security and reduce turnaround time (TAT) of the maintenance process it is important to get as much engine data as possible before disassembly. Aero engines are especially subjected to environmental and operational influences. For the high pressure turbine (HPT), the following parameters have been identified to describe the deterioration of its nozzle guide vane (NGV): On-wing cycles, NGV material, airport region, engine wing position, thrust rating, vane repair history and customer business segment. The combined influences of the parameters are non-trivial and it is not possible to acquire them analytically. There are no known mathematical laws connecting the above-mentioned parameters. The linear regression method set limits for processing data in an adequate manner. This is confirmed by the analysis of the arithmetic means and standard deviations. Especially the standard deviation values fit in a broad spectrum due to various reasons. Thus, it is not feasible to make an appropriate forecast with a simple statistical method due to the multidimensional character of the parameters influencing the accuracy. For this reason, advanced methods need to be developed to derive a feasible forecast method. By applying a statistical hypothesis test, a bayesian belief network (BBN) has been designed. It allows the use of imprecise data without suffering a significant loss in forecast accuracy and additionally, the implementation of expert knowledge. The objective of this study is to develop an effective BBN in order to adequately predict the next repair of the first stage HPT NGV of the General Electric CF6-80C2 engine. The reason for selecting the NGV is due to its high susceptibility to different influences, combined with the significant costs and TAT during the maintenance process. Having poor forecasting quality by using a simple statistical method, the evaluation of the BBN provides very satisfactory accuracy of above 80 percent which is equivalent to 19 out of 23 vane segments. Furthermore, the developed BBN emphasises robustness when detecting the expected tendencies while having only a limited amount of input parameters. Further work includes application of this method on other engine components as well as establishing the business value of the developed method. In conclusion, BBN have tremendous potential for forecasting the repair of the entire jet engine.

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Guan, Mark, Patrick Kirchen, Steven Rogak, and Patrick Steiche. "Development of a Low-Cost Exhaust H2 Measurement Method for In-Use Vehicles." In ASME 2021 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/icef2021-67633.

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Abstract Port-injected hydrogen (H2) can be used as a partial substitution of diesel fuel in compression-ignition engines to reduce GHG emissions. For port-injected H2 systems, incomplete combustion or valve overlap can result in H2 slip, which increases the brake-specific fuel consumption. In this study, a low-cost method is developed to measure the H2 slip in the exhaust of a heavy-duty truck under real-world operating conditions. The truck is equipped with a 2016 15L Detroit diesel engine converted to run in dual-fuel mode with port-injected H2 ignited by directly injected diesel. Existing H2 detecting methods used for steady-state laboratory tests either have slow response time or require well-controlled testing environments. To develop a method suitable for transient on-road H2 measurements, we utilized a low-cost semiconductor sensor. The output of the sensor is potentially influenced by temperature, relative humidity (RH), gas flow rate, as well as the sensor’s resistance in the ambient air (R0) and the pre-heating strategy. Firstly, the characteristics of R0 was investigated in controlled benchtop tests, where pre-heating time, gas temperature, and RH were monitored. Then, the sensor was calibrated using a standard gas mixture of H2 and nitrogen. Finally, a Portable Emission Measurement System (PEMS) was developed to control the conditions of the sample gas. The sensor output was recorded using a low-cost Raspberry Pi Data Acquisition (DAQ) system in combination with an analog HAT (Hardware attached on top) module at a frequency of 4Hz. The results from the benchtop tests show that RH and flow rate both have significant influences on the sensor’s output. To ensure a stable R0, thirty minutes of pre-heating time is required. After calibration, the sensor’s readings are within 15% difference compared with the actual values. Data from the on-road tests demonstrated the applicability of the system for in-use vehicle’s exhaust H2 measurement. It was found from this data that the sensor’s average response time to rising H2 concentrations is 4.5s, but that the response to decreasing concentrations is much slower. The exhaust H2 concentrations, together with the engine operating data, were used to generate H2 emission maps, which provide insight into the relationship between the engine load, engine speed and the H2 slip. With further sensor development and sample gas control, this method can achieve high accuracy and extended application in in-use vehicle’s H2 emission measurements.

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Ikica, Andrej, and Peter Peer. "Influence of image quality on SWT voting-based color reduction method for detecting text in natural scene images." In 2014 International Work Conference on Bio-Inspired Intelligence (IWOBI). IEEE, 2014. http://dx.doi.org/10.1109/iwobi.2014.6913954.

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Liang, Xin, Dawei Cheng, Fangzhou Yang, Yifeng Luo, Weining Qian, and Aoying Zhou. "F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/619.

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The share prices of listed companies in the stock trading market are prone to be influenced by various events. Performing event detection could help people to timely identify investment risks and opportunities accompanying these events. The financial events inherently present hierarchical structures, which could be represented as tree-structured schemes in real-life applications, and detecting events could be modeled as a hierarchical multi-label text classification problem, where an event is designated to a tree node with a sequence of hierarchical event category labels. Conventional hierarchical multi-label text classification methods usually ignore the hierarchical relationships existing in the event classification scheme, and treat the hierarchical labels associated with an event as uniform labels, where correct or wrong label predictions are assigned with equal rewards or penalties. In this paper, we propose a neural hierarchical multi-label text classification method, namely F-HMTC, for a financial application scenario with massive event category labels. F-HMTC learns the latent features based on bidirectional encoder representations from transformers, and directly maps them to hierarchical labels with a delicate hierarchy-based loss layer. We conduct extensive experiments on a private financial dataset with elaborately-annotated labels, and F-HMTC consistently outperforms state-of-art baselines by substantial margins. We will release both the source codes and dataset on the first author's repository.

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Bedotti, Andrea, Mirko Pastori, Antonio Lettini, and Paolo Casoli. "Condition Monitoring Based on Thermodynamic Efficiency Method for an Axial Piston Pump." In BATH/ASME 2018 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fpmc2018-8808.

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In the last years, the interest in the field of Prognostics and Health Management (PHM) has been growing in many industrial fields. The objective of PHM is to switch from a time-based (scheduled) maintenance to a predictive maintenance with advantages in terms of reliability and safety. This paper presents the thermodynamic method for the fault detection of an axial piston pump which is a critical component in many hydraulic systems; the method was developed for the evaluation of the overall efficiency which is an important parameter to monitor the machine health state. Through the measurements of temperatures and pressures at suction and delivery ports the method allows to calculate the efficiency avoiding the use of costly sensors, such as speed and torque sensors. The paper investigates the possibility of utilizing the pump overall efficiency evaluated through the thermodynamic method as a reliable parameter for the fault detection. The machine under study is a variable displacement axial-piston pump with external drainage equipped with a load sensing regulator. The thermodynamic method was already validated in a previous work by comparing it with the standard approach, based on the direct measurement of the mechanical power. The proposed method requires the measurement of the delivery and drain flow rates involving the use of expensive flowmeters which could prevent its usage in online applications; this limit should be overcome with the development of low-cost solutions for flow rate measurements. A preliminary investigation of the pump failure modes was conducted to identify the most important faults which need to be considered. An experimental campaign was carried out on a laboratory test bench with the pump in the flawless state and in faulty states. The faulty states were realized by introducing components with artificial faults into the pump. The pump was accurately instrumented to monitor all the main variables, i.e. pressures, temperatures, flow rates, swash plate angle and shaft torque and speed. Different operating conditions were considered and each test was repeated several times in order to acquire a suitable population to verify the repeatability of the data. The experiments demonstrate the method capability of detecting some but not all of the incipient faults tested in steady-state conditions as a consequence of temperature variations which have the most important influence on efficiency estimation. Future works will include the development of innovative solutions to measure flow-rates and the testing of other faults to further verify the reliability of the method.

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Звіти організацій з теми "Method of detecting influences"

Paller, M. H., R. C. Tuckfield, and W. M. Starkel. Statistical methods for detecting ichthyoplankton density patterns that influence entrainment mortality. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/221923.

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Henderson, Kevin. Optical Method for Detecting Alpha Particles and Neutrons. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1214634.

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Henderson, Kevin. Optical Method for Detecting and Analyzing Energetic Particle Radiation. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1214632.

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Downing, D. J., W. F. Lawkins, M. D. Morris, and G. Ostrouchov. A method for detecting changes in long time series. Office of Scientific and Technical Information (OSTI), September 1995. http://dx.doi.org/10.2172/161513.

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Huang, G., S. Beaulieu, and D. Rochefort. A Traffic-Based Method of Detecting Dead Internet Key Exchange (IKE) Peers. RFC Editor, February 2004. http://dx.doi.org/10.17487/rfc3706.

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Rogers, III, Gregory John G., and Jason M. Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR. Fort Belvoir, VA: Defense Technical Information Center, January 2015. http://dx.doi.org/10.21236/ada612636.

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Miles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber, and Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.

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In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were studied and a relationship was derived. It was found that using a ratio of two wavelenght reflectance images (750nm and 670nm) it was possible to segment the plants from the background. Once ths was accomplished it was then possible to classify the segmented images into weed or crop by use of the neural network. The neural network developed for this work is a modification of the standard learning vector quantization algorithm. This neural network was modified by replacing the time-varying adaptation gain with a constant adaptation gain and a binary reinforcement function. This improved accuracy and training time as well as introducing several new properties such as hill climbing and momentum addition. The network was trained and tested with different wavelength combinations in order to find the best results. Finally, the results of the classifier were evaluated using a pixel based method and a block based method. In the pixel based method every single pixel is evaluated to test whether it was classified correctly or not and the best weed classification results were 81% and its associated crop classification accuracy is 57%. In the block based classification method, the image was divided into blocks and each block was evaluated to determine whether they contained weeds or not. Different block sizes and thesholds were tested. The best results for this method were 97% for a block size of 8 inches and a pixel threshold of 60. A simulation model was developed to 1) quantify the effectiveness of a site-specific sprayer, 2) evaluate influence of diffeent design parameters on efficiency of the site-specific sprayer. In each iteration of this model, infected areas (weed patches) in the field were randomly generated and the amount of required herbicides for spraying these areas were calculated. The effectiveness of the sprayer was estimated for different stain sizes, nozzle types (conic and flat), nozzle sizes and stain detection levels of the identification system. Simulation results indicated that the flat nozzle is much more effective as compared to the conic nozzle and its relative efficiency is greater for small nozzle sizes. By using a site-specific sprayer, the average ratio between the spraying areas and the stain areas is about 1.1 to 1.8 which can save up to 92% of herbicides, especially when the proportion of the stain areas is small.

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Hovav, Ran, Peggy Ozias-Akins, and Scott A. Jackson. The genetics of pod-filling in peanut under water-limiting conditions. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597923.bard.

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Pod-filling, an important yield-determining stage is strongly influenced by water stress. This is particularly true for peanut (Arachishypogaea), wherein pods are developed underground and are directly affected by the water condition. Pod-filling in peanut has a significant genetic component as well, since genotypes are considerably varied in their pod-fill (PF) and seed-fill (SF) potential. The goals of this research were to: Examine the effects of genotype, irrigation, and genotype X irrigation on PF and SF. Detect global changes in mRNA and metabolites levels that accompany PF and SF. Explore the response of the duplicate peanut pod transcriptome to drought stress. Study how entire duplicated PF regulatory processes are networked within a polyploid organism. Discover locus-specific SNP markers and map pod quality traits under different environments. The research included genotypes and segregating populations from Israel and US that are varied in PF, SF and their tolerance to water deficit. Initially, an extensive field trial was conducted to investigate the effects of genotype, irrigation, and genotype X irrigation on PF and SF. Significant irrigation and genotypic effect was observed for the two main PF related traits, "seed ratio" and "dead-end ratio", demonstrating that reduction in irrigation directly influences the developing pods as a result of low water potential. Although the Irrigation × Genotype interaction was not statistically significant, one genotype (line 53) was found to be more sensitive to low irrigation treatments. Two RNAseq studies were simultaneously conducted in IL and the USA to characterize expression changes that accompany shell ("source") and seed ("sink") biogenesis in peanut. Both studies showed that SF and PF processes are very dynamic and undergo very rapid change in the accumulation of RNA, nutrients, and oil. Some genotypes differ in transcript accumulation rates, which can explain their difference in SF and PF potential; like cvHanoch that was found to be more enriched than line 53 in processes involving the generation of metabolites and energy at the beginning of seed development. Interestingly, an opposite situation was found in pericarp development, wherein rapid cell wall maturation processes were up-regulated in line 53. Although no significant effect was found for the irrigation level on seed transcriptome in general, and particularly on subgenomic assignment (that was found almost comparable to a 1:1 for A- and B- subgenomes), more specific homoeologous expression changes associated with particular biosynthesis pathways were found. For example, some significant A- and B- biases were observed in particular parts of the oil related gene expression network and several candidate genes with potential influence on oil content and SF were further examined. Substation achievement of the current program was the development and application of new SNP detection and mapping methods for peanut. Two major efforts on this direction were performed. In IL, a GBS approach was developed to map pod quality traits on Hanoch X 53 F2/F3 generations. Although the GBS approach was found to be less effective for our genetic system, it still succeeded to find significant mapping locations for several traits like testa color (linkage A10), number of seeds/pods (A5) and pod wart resistance (B7). In the USA, a SNP array was developed and applied for peanut, which is based on whole genome re-sequencing of 20 genotypes. This chip was used to map pod quality related traits in a Tifrunner x NC3033 RIL population. It was phenotyped for three years, including a new x-ray method to phenotype seed-fill and seed density. The total map size was 1229.7 cM with 1320 markers assigned. Based on this linkage map, 21 QTLs were identified for the traits 16/64 weight, kernel percentage, seed and pod weight, double pod and pod area. Collectively, this research serves as the first fundamental effort in peanut for understanding the PF and SF components, as a whole, and as influenced by the irrigation level. Results of the proposed study will also generate information and materials that will benefit peanut breeding by facilitating selection for reduced linkage drag during introgression of disease resistance traits into elite cultivars. BARD Report - Project4540 Page 2 of 10

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Burnison, Shaughn, Amanda Livers-Douglas, Cesar Barajas-Olalde, Lu Jin, Heidi Vettleson, John Hamiling, and Charles Gorecki. Final report of a scalable, automated, semipermanent seismic array (SASSA) method for detecting CO₂ extent during geologic CO₂ injection. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1413495.

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Kirichek, Galina, Vladyslav Harkusha, Artur Timenko, and Nataliia Kulykovska. System for detecting network anomalies using a hybrid of an uncontrolled and controlled neural network. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3743.

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In this article realization method of attacks and anomalies detection with the use of training of ordinary and attacking packages, respectively. The method that was used to teach an attack on is a combination of an uncontrollable and controlled neural network. In an uncontrolled network, attacks are classified in smaller categories, taking into account their features and using the self- organized map. To manage clusters, a neural network based on back-propagation method used. We use PyBrain as the main framework for designing, developing and learning perceptron data. This framework has a sufficient number of solutions and algorithms for training, designing and testing various types of neural networks. Software architecture is presented using a procedural-object approach. Because there is no need to save intermediate result of the program (after learning entire perceptron is stored in the file), all the progress of learning is stored in the normal files on hard disk.

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